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容器云资源调度策略的改进 被引量:13

Improved Container Cloud Resource Scheduling Policy
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摘要 为了均衡利用容器云集群的资源,对Mesos的资源调度策略做了改进。改进的资源调度策略是在原有调度策略的基础上,把Mesos-Slave节点的CPU使用率、内存的占有率以及运行的容器个数考虑进去,并对三者加权来做为接下来资源调度的依据。最后通过改进前后集群资源利用率的对比,验证了改进后资源调度策略能够使集群资源利用率趋于均衡。 In order to balance the use of container cloud cluster resources,the resource scheduling strategy of Mesos made improvements. Improved resource scheduling policy is based on the original scheduling policy and the CPU usage,share memory and the number of containers of Mesos-Slave nodes run into account,and to do for the next three weighted resource scheduling in accordance with. Finally,by comparing before and after the cluster improved resource utilization,validate the improved resource scheduling strategy can make the cluster resource utilization tends to be balanced.
出处 《计算机与数字工程》 2017年第10期1931-1936,共6页 Computer & Digital Engineering
关键词 容器云 集群资源利用率 资源调度策略 container cloud cluster resource utilization resource management strategy
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  • 1徐童,廖建新.基于分段线性函数的广义效用max-min公平分配算法研究[J].通信学报,2006,27(10):25-30. 被引量:4
  • 2孟宪福.分布式环境下任务调度模型研究[J].大连理工大学学报,2006,46(6):920-925. 被引量:6
  • 3袁亚湘 孙文渝.最优化理论与方法[M].北京:科学出版社,1999..
  • 4Buyya R, Yeo C S, Venugopal S, et al. Cloud computing and e-merging IT platforms: vision, hype, and reality for delivering computing as the 5th utility[J]. Future Generation Computer Systems,2009,25(6) :599-616.
  • 5Armbrust M, Fox A, Griffith R, et al. Above the Clouds: A Berkeley View of Cloud Computing [EB/OL]. http..//www, ee- cs. berkeley, edu/Pubs/TechRpts/2009/EECS-2009-28, html, February 2009.
  • 6Lin Wei-wei, Qi De-yu. Research on Resource Self-Organizing Model for Cloud Computing[C]// 2010 International Conference on Internet Technology and Applications. 2010:1-5.
  • 7Von L G, Wang L, Younge A J, et al. Power-Aware Scheduling of Virtual Machines in DVFS-enabled Clusters[C] ff Proc. of IEEE International Conference on Cluster Computing 2009. New Orleans, LA, USA, 2009 : 1-10.
  • 8Ge R, Feng X, Cameron K. Performance-constrained distributed dvs scheduling for scientific applications on power-aware clus ters[C]//Proceedings of the 2005 ACM/IEEE Conference on Supercomputing. IEEE Computer Society, Washington DC, USA, 2005 : 34.
  • 9Venkatachalam V, Franz M. Power reduction techniques for mi- croprocessor systems[J]. ACM Computing Surveys (CSUR), 2005,37(3) : 195-237.
  • 10Mezmaz M, MelabN, KessaciY, etal. Aparallel bi-objective hy- brid metaheuristic for energy-aware scheduling for cloud compu- ting systems[J]. Journal of Parallel and Distributed Computing (JPDC), 2011,71(11) : 1497-1508.

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